The MIXED Procedure

Syntax: MIXED Procedure

The following statements are available in the MIXED procedure:

PROC MIXED <options> ;
BY variables ;
CLASS variable <(REF= option)> …<variable <(REF= option)>> </ global-options> ;
CODE <options> ;
ID variables ;
MODEL dependent = <fixed-effects> </ options> ;
RANDOM random-effects </ options> ;
REPEATED <repeated-effect> </ options> ;
PARMS (value-list)…</ options> ;
PERFORMANCE <options> ;
PRIOR <distribution> </ options> ;
CONTRAST ’label’ <fixed-effect values …>
<|random-effect values …>, …</ options> ;
ESTIMATE ’label’ <fixed-effect values …>
<|random-effect values …> </ options> ;
LSMEANS fixed-effects </ options> ;
LSMESTIMATE model-effect lsmestimate-specification </ options> ;
SLICE model-effect </ options> ;
STORE <OUT=>item-store-name </ LABEL='label'> ;
WEIGHT variable ;

Items within angle brackets ( < > ) are optional. The CONTRAST, ESTIMATE, LSMEANS, and RANDOM statements can appear multiple times; all other statements can appear only once.

The PROC MIXED and MODEL statements are required, and the MODEL statement must appear after the CLASS statement if a CLASS statement is included. The CONTRAST, ESTIMATE, LSMEANS, RANDOM, and REPEATED statements must follow the MODEL statement. The CONTRAST and ESTIMATE statements must also follow any RANDOM statements. The LSMESTIMATE, SLICE, and STORE statements are shared with many procedures. Summary descriptions of functionality and syntax for these statements are also given after the PROC MIXED statement in alphabetical order, but you can find full documentation on them in Chapter 19: Shared Concepts and Topics.

Table 59.1 summarizes the basic functions and important options of each PROC MIXED statement. The syntax of each statement in Table 59.1 is described in the following sections in alphabetical order after the description of the PROC MIXED statement.

Table 59.1: Summary of PROC MIXED Statements

Statement	Description	Options
PROC MIXED	Invokes the procedure	DATA= specifies input data set, METHOD= specifies estimation method
BY	Performs multiple PROC MIXED analyses in one invocation	None
CLASS	Declares qualitative variables that create indicator variables in design matrices	None
CODE	Requests that the procedure write SAS DATA step code to a file or catalog entry	FILE= names the file where the generated code is saved, CATALOG= names the catalog entry where the generated code is saved, IMPUTE imputes predicted values for observations with missing or invalid covariates, RESIDUAL computes residuals
ID	Lists additional variables to be included in predicted values tables	None
MODEL	Specifies dependent variable and fixed effects, setting up $\mb {X}$	S requests solution for fixed-effects parameters, DDFM= specifies denominator degrees of freedom method, OUTP= outputs predicted values to a data set, INFLUENCE computes influence diagnostics
RANDOM	Specifies random effects, setting up $\mb {Z}$ and $\mb {G}$	SUBJECT= creates block-diagonality, TYPE= specifies covariance structure, S requests solution for random-effects parameters, G displays estimated $\mb {G}$
REPEATED	Sets up $\mb {R}$	SUBJECT= creates block-diagonality, TYPE= specifies covariance structure, R displays estimated blocks of $\mb {R}$ , GROUP= enables between-subject heterogeneity, LOCAL adds a diagonal matrix to $\mb {R}$
PARMS	Specifies a grid of initial values for the covariance parameters	HOLD= and NOITER hold the covariance parameters or their ratios constant, PARMSDATA= reads the initial values from a SAS data set
PERFORMANCE	Specifies the number of threads to use	NTHREADS=
PRIOR	Performs a sampling-based Bayesian analysis for variance component models	NSAMPLE= specifies the sample size, SEED= specifies the starting seed
CONTRAST	Constructs custom hypothesis tests	E displays the $\mb {L}$ matrix coefficients
ESTIMATE	Constructs custom scalar estimates	CL produces confidence limits
LSMEANS	Computes least squares means for classification fixed effects	DIFF computes differences of the least squares means, ADJUST= performs multiple comparisons adjustments, AT changes covariates, OM changes weighting, CL produces confidence limits, SLICE= tests simple effects
LSMESTIMATE	Provides custom hypothesis tests among the least squares means	ADJUST= determines the method for multiple comparison adjustment of LS-mean differences, JOINT requests a joint F or chi-square test for the rows of the estimate
SLICE	Performs a partitioned analysis of LS–means for an interaction	ADJUST= determines the method for multiple comparison adjustment of LS-mean differences, DIFF requests differences of LS-means
STORE	Saves the context and results of the analysis	LABEL= adds a custom label
WEIGHT	Specifies a variable by which to weight $\mb {R}$	None